AI
Microsoft gave Office to students for nearly nothing, not as charity but as customer acquisition cost arbitrage. Four years of muscle memory did the selling, and enterprise licenses followed for three decades. Something structurally similar is happening to dev tools, except the conversion funnel has collapsed from years to minutes
AI
Vibe coding gets you to a working prototype faster than anything before it. The part that trips teams up is the handoff. The pattern shows up consistently now. Someone spends a weekend prompting their way to a functional app. The demo lands well, leadership sees velocity, and engineering gets the
AI
Howard Marks' new AI memo buries its most important observation in a quote from Claude: if 30-50% of structured knowledge work migrates to AI compute, that's $150-250B in annual labor value shifting. The market already priced this in, violently. The SaaSpocalypse erased roughly $1T in enterprise software
AI
The fastest way to understand AI isn't to study it. It's to build something small that solves a problem you actually have, not a tutorial project or a course, but something you'll use tomorrow morning. A script that sorts your email backlog by urgency.
AI
Last week I asked Claude to generate architecture documentation for a system I'd built. The system is called naalayiram — an AI-powered exploration platform for 4,000 ancient Tamil poems. Claude produced a 16-page PDF with embedded diagrams, then a comprehensive architecture PNG when I wasn't satisfied
AI
Claude Sonnet 4.6 dropped on February 17th. By that evening I had run a full evaluation and decided to stay on 4.5. Over the next two days, I ran the same pipeline a dozen more times across both models. The answer didn't change. What I tested
AI
The S&P 500 software sub-index is down 27% since October. Private equity firms are tripping over each other to downplay their software exposure. The Economist reports $500 billion in software-linked debt lurking in US credit markets. And "SaaS is dead" is having its moment as a
AgenticCommerce
TL;DR: If AI assistants can reinterpret product flaws as features based on your specific goals, that changes everything. When Gemini recommended socks that hikers panned (loose elastic is bad for hiking but good for circulation), it demonstrated what could be goal-aware inference. If this capability scales, it threatens the
AI
Here's something I've noticed after months of heavy use: Claude handles file operations with surprising reliability. ChatGPT... doesn't. Not consistently, anyway. I'm not talking about edge cases. I mean simple requests - "export this as markdown," "give me a
AI
The Problem "Which LLM is best?" is the wrong question. "Best for what?" is the right one. Traditional evals tell you which model is smartest. This tells you which model is right for your specific task. Every model has a design philosophy - a personality that
SystemsThinking
How OpenAI rewired the economics of compute through two feedback loops I love seeing systems loops in action. Feedback mechanisms reveal how complex systems actually work. And right now, we're witnessing two of the most elegant — and opposite — capital loops ever engineered in tech In the span of